![]() |
市场调查报告书
商品编码
1755967
2032 年分类和空间优化市场预测:按解决方案、部署模式、应用和区域进行的全球分析Assortment and Space Optimization Market Forecasts to 2032 - Global Analysis By Solution, Deployment Mode, Application and By Geography |
根据 Stratistics MRC 的数据,全球分类和空间优化市场预计在 2025 年达到 23.6 亿美元,预计到 2032 年将达到 53.5 亿美元,预测期内的复合年增长率为 12.42%。
选择理想的产品组合(商品组合)并将其有效地安排在可用的零售空间中(空间优化),以优化销售额和客户满意度,这一策略流程被称为「商品组合和空间优化」。决定在商店或线上销售哪些产品、数量以及在何处摆放,需要考虑顾客需求、产品性能和可用空间。最终,该策略能够帮助零售商提高存货周转、减少缺货并改善购物体验,进而盈利和营运效率。
数据主导零售规划的需求不断增加
零售商越来越多地使用进阶分析来了解顾客的偏好和行为。这使他们能够更好地根据目标市场定製商品组合,从而提高顾客满意度和销售额。优化的空间配置可以降低库存成本并提高货架效率。数据驱动的洞察还能使零售商快速回应季节和市场趋势。这项策略提升了零售业的竞争优势和营运效率。
部署成本高且整合复杂
由于技术、软体和熟练员工所需的巨额支出,财务障碍随之而来。这些解决方案必须与现有的IT基础设施无缝集成,而整合的复杂性又进一步增加了难度。这种复杂性增加了实施时间,并增加了业务中断的可能性。企业可能面临人员配备、系统相容性和资料迁移方面的挑战。这些因素共同降低了接受度,并阻碍了消费者的投资。
全通路零售的兴起
技术、软体和熟练员工所需的巨额支出造成了财务障碍。这些解决方案必须与现有的IT基础设施无缝集成,这又增加了整合的复杂性。这种复杂性增加了业务中断的可能性,并延长了实施时间。公司可能在员工培训、系统相容性和资料迁移方面遇到困难。这些因素共同限制了采用率,阻碍了消费者投资,并阻碍了更广泛的市场扩张。
资料隐私问题和监管压力
由于遵守CCPA和GDPR等法规带来的营运复杂性和成本增加,技术采用速度放缓。这些法律约束限制了资料分析的广度和深度,从而降低了最佳化解决方案的准确性。许多组织也难以获得客户同意并维护资料安全,这可能会延迟计划执行。此外,一些参与者由于担心製裁和声誉受损,不愿充分利用先进的数据驱动技术。整体而言,资料隐私法是阻碍产业创新和繁荣发展的一大障碍。
COVID-19的影响
新冠疫情扰乱了全球零售营运、供应链和消费行为,对商品组合和空间优化市场产生了重大影响。零售商在管理库存和根据需求突变调整商品组合方面面临挑战。门市关闭和客流量减少加速了对数据主导的空间优化工具的需求。在电子商务蓬勃发展的背景下,企业采用先进的分析和人工智慧主导的解决方案来改善货架规划和商品组合策略,确保在快速变化的零售环境中保持业务效率和客户满意度。
预测期内,分类优化部分预计将实现最大幅度成长
预计品类优化细分市场将在预测期内占据最大市场占有率,这得益于能够为客户带来最大盈利的合理商品组合。该细分市场透过专注于高需求商品并最大程度减少无利可图的库存来提高存货周转。此外,该细分市场还透过根据当地偏好进行商品组合来提高客户满意度。品类优化中的高阶数据分析和人工智慧主导的洞察有助于企业降低成本并提高销售效率。整体而言,品类优化能够更好地利用空间,从而提高零售环境中的收益和业务效率。
预计在预测期内,产品置入和商品行销部分将以最高的复合年增长率成长。
产品摆放与商品行销领域预计将在预测期内实现最高成长率,这得益于其能够提升产品在零售空间的可见度和消费者参与度。有效的摆放策略能够最大限度地提高零售商的货架利用率,从而优化空间配置并改善库存管理。商品行销策略能够影响购买行为,提高销售额,并实现更精准的需求预测。这些方法还支援根据消费者偏好和季节性趋势进行动态商品组合调整,有助于提高零售环境中的业务效率和盈利。
预计亚太地区将在预测期内占据最大的市场占有率,这得益于都市化加快、零售店面不断扩大以及对即时库存可视性需求的不断增长。印度和东南亚等新兴经济体正在采用空间规划技术,以应对零售空间有限和消费行为变化的问题。云端基础的商品分类工具因其扩充性和成本效益而日益普及。市场参与者正在与当地零售商合作,制定符合当地文化的最佳化策略,而智慧型手机的普及则推动着行动零售分析和店内决策效率的提升。
预计北美地区在预测期内的复合年增长率最高,这得益于其发达的零售基础设施、日益普及的电商以及整个零售链中数据分析的广泛应用。零售商正在利用人工智慧解决方案来优化货架配置、加强库存管理并提升客户体验。该地区的技术供应商数量众多,数位转型投资也持续成长。主要参与者正专注于整合机器学习和规划工具,以根据当地消费者偏好调整产品组合,并最大化每平方英尺的盈利。
According to Stratistics MRC, the Global Assortment and Space Optimization Market is accounted for $2.36 billion in 2025 and is expected to reach $5.35 billion by 2032 growing at a CAGR of 12.42% during the forecast period. The strategic process of choosing the ideal product mix (assortment) and effectively arranging them in the available retail space (space optimisation) in order to optimise sales and customer happiness is known as "assortment and space optimisation." To decide which products to offer, in what number, and where to put them in-store or online, it entails examining customer demand, product performance, and available space. In the end, this strategy increases profitability and operational efficiency across a range of retail formats by assisting retailers in improving inventory turnover, decreasing stockouts, and improving the shopping experience.
Rising demand for data-driven retail planning
Advanced analytics are being used by retailers more and more to comprehend the preferences and behaviour of their customers. This makes it possible to create a precise product assortment that is suited to the target market, increasing customer happiness and sales. Allocating space optimally lowers inventory costs and increases shelf efficiency. Retailers may also swiftly adjust to seasonal shifts and market trends with the use of data-driven insights. All things considered, this strategy improves competitive advantage and operational efficiency in the retail industry.
High implementation cost and integration complexity
A financial barrier is created by the significant expenditure needed for technology, software, and qualified staff. Since these solutions must integrate seamlessly with the current IT infrastructure, integration complexity adds still another level of difficulty. Longer deployment durations and a greater likelihood of operational disruptions can result from this complexity. Businesses may have difficulties with personnel training, system compatibility, and data migration. These elements work together to limit acceptance and lower consumer willingness to invest, which impedes broad market expansion.
Emergence of omnichannel retailing
A financial barrier is created by the significant expenditure needed for technology, software, and qualified staff. Since these solutions must integrate seamlessly with the current IT infrastructure, integration complexity adds still another level of difficulty. Longer deployment durations and a greater likelihood of operational disruptions can result from this complexity. Businesses may have difficulties with personnel training, system compatibility, and data migration. These elements work together to limit acceptance and lower consumer willingness to invest, which impedes broad market expansion.
Data privacy concerns and regulatory pressures
Adoption of technology is slowed by the increased operational complexity and expenses associated with complying with regulations such as the CCPA and GDPR. The breadth and depth of data analytics are constrained by these legal constraints, which lowers the precision of optimisation solutions. Project execution may be delayed because organisations frequently struggle to secure client consent and maintain data security. Furthermore, some participants are deterred from utilising sophisticated data-driven technologies to their full potential due to concerns about sanctions and reputational harm. In general, privacy laws erect obstacles that impede this industry's ability to innovate and thrive.
Covid-19 Impact
The Covid-19 pandemic significantly impacted the Assortment and Space Optimization Market by disrupting global retail operations, supply chains, and consumer behavior. Retailers faced challenges in inventory management and adapting product assortments to sudden shifts in demand. Store closures and reduced foot traffic accelerated the need for data-driven space optimization tools. As e-commerce surged, businesses adopted advanced analytics and AI-driven solutions to improve shelf planning and assortment strategies, ensuring operational efficiency and customer satisfaction in a rapidly changing retail environment.
The assortment optimization segment is expected to be the largest during the forecast period
The assortment optimization segment is expected to account for the largest market share during the forecast period, due to the most profitable and relevant product mix for their customers. It enhances inventory turnover by focusing on high-demand items while minimizing underperforming stock. This segment also improves customer satisfaction through tailored assortments that meet local preferences. Advanced data analytics and AI-driven insights in assortment optimization help businesses reduce costs and increase sales efficiency. Overall, assortment optimization drives better space utilization, boosting both revenue and operational effectiveness in retail environments.
The product placement & merchandising segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the product placement & merchandising segment is predicted to witness the highest growth rate by enhancing product visibility and consumer engagement within retail spaces. Effective placement strategies help retailers maximize shelf utilization, leading to optimized space allocation and improved inventory management. Merchandising tactics influence buying behavior, driving higher sales and enabling better demand forecasting. These approaches also support dynamic assortment adjustments based on consumer preferences and seasonal trends. Consequently, they contribute to increased operational efficiency and profitability in retail environments.
During the forecast period, the Asia Pacific region is expected to hold the largest market share fuelled by rising urbanization, retail expansion, and increasing demand for real-time inventory visibility. Emerging economies like India and Southeast Asia are adopting space planning technologies to handle limited retail space and changing consumer behaviour. Cloud-based assortment tools are gaining popularity due to their scalability and cost-effectiveness. Market players are collaborating with local retailers to develop culturally tailored optimization strategies, while growing smartphone penetration enhances mobile retail analytics and in-store decision-making efficiency.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to the advanced retail infrastructure, strong e-commerce adoption, and widespread use of data analytics across retail chains. Retailers leverage AI-driven solutions to optimize shelf layouts, enhance inventory management, and improve customer experience. The region sees strong presence of tech vendors and consistent investment in digital transformation. Key players are focused on integrating machine learning with planogramming tools to tailor product assortment based on regional consumer preferences and maximize profitability per square foot.
Key players in the market
Some of the key players profiled in the Assortment and Space Optimization Market include Oracle Corporation, SAP SE, Blue Yonder Group Inc., RELEX Solutions, SymphonyAI, Accenture plc, McKinsey & Company Inc., Microsoft Corporation, Nielsen Holdings plc, Aptos LLC, Invent Analytics LLC, Tata Consultancy Services Limited (TCS), Antuit.ai, Trax Inc., ToolsGroup Inc., Solteq plc and DotActiv Ltd.
In March 2025, Oracle was recognized as a Leader in the 2025 IDC MarketScape for AI-driven Retail Assortment Planning Solutions. The report highlighted Oracle's AI-powered advanced SKU prioritization and assortment optimization capabilities, noting active results in cost savings and strong partnerships in developing new assortment optimization methods.
In June 2024, SAP acquired WalkMe, a digital adoption platform, for $1.5 billion. This acquisition aims to enhance user experience and adoption of SAP solutions, including those related to assortment and space optimization.
In March 2023, SAP partnered with Axfood, Sweden's second-largest food retailer, to develop an advanced assortment planning solution. This collaboration aimed to create a user-friendly system that integrates data from sales histories, forecasts, and customer insights, enhancing decision-making processes and reducing product wastage.